Haptic Interactions Subject to Variable Latency.

Model-Mediated Teleoperation (MMT) between a haptic device and a remote or virtual environment uses a local model of the environment to compensate for latency of communication. MMT is often case-specific, and requires underlying latency distributions to be known. We propose a novel approach - which we refer to as the DelayRIM - which uses the time-stepping aspect of a Reduced Interface Model for the environment to render an up-to-date force to the haptic device from the delayed information. RIM is applicable to any physical or virtual system, and the DelayRIM itself makes no underlying assumption about the latency distribution. We show that for realistic variable delays, the DelayRIM improves transparency compared to other methods for a virtual drone bilateral teleoperation scenario.

Seasonal food webs with migrations: multi-season models reveal indirect species interactions in the Canadian Arctic tundra.

Models incorporating seasonality are necessary to fully assess the impact of global warming on Arctic communities. Seasonal migrations are a key component of Arctic food webs that still elude current theories predicting a single community equilibrium. We develop a multi-season model of predator-prey dynamics using a hybrid dynamical systems framework applied to a simplified tundra food web (lemming-fox-goose-owl). Hybrid systems models can accommodate multiple equilibria, which is a basic requirement for modelling food webs whose topology changes with season. We demonstrate that our model can generate multi-annual cycling in lemming dynamics, solely from a combined effect of seasonality and state-dependent behaviour. We compare our multi-season model to a static model of the predator-prey community dynamics and study the interactions between species. Interestingly, including seasonality reveals indirect interactions between migrants and residents not captured by the static model. Further, we find that the direction and magnitude of interactions between two species are not necessarily accurate using only summer time-series. Our study demonstrates the need for the development of multi-season models and provides the tools to analyse them. Integrating seasonality in food web modelling is a vital step to improve predictions about the impacts of climate change on ecosystem functioning. This article is part of the theme issue 'The changing Arctic Ocean: consequences for biological communities, biogeochemical processes and ecosystem functioning'.

Author Correction: Effect of diversity on growth, mortality, and loss of resilience to extreme climate events in a tropical planted forest experiment.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Effect of diversity on growth, mortality, and loss of resilience to extreme climate events in a tropical planted forest experiment.

A pressing question is whether biodiversity can buffer ecosystem functioning against extreme climate events. However, biodiversity loss is expected to occur due to climate change with severe impacts to tropical forests. Using data from a ca. 15 year-old tropical planted forest, we construct models based on a bootstrapping procedure to measure growth and mortality among different species richness treatments in response to extreme climate events. In contrast to higher richness mixtures, in one-species plots we find growth is strongly regulated by climate events and we also find increasingly higher mortality during a consecutive four year dry event. Based on these results together with indicators of loss of resilience, we infer an effect of diversity on critical slowing down. Our work generates new methods, concepts, and applications for global change ecology and emphasises the need for research in the area of biodiversity-ecosystem functioning along environmental stress gradients.